Digital Image Processing
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EE368/CS232: Digital Image Processing
Monday, Wednesday, Friday
9:30am - 10:45am during the first 7 weeks of the quarter
Image sampling and quantization, color, point operations, segmentation, morphological image processing, linear image filtering and correlation, image transforms, eigenimages, multiresolution image processing, noise reduction and restoration, feature extraction and recognition tasks, image registration. Emphasis is on the general principles of image processing. Students learn to apply material by implementing and investigating image processing algorithms in Matlab and optionally on Android mobile devices. Term project. In the fall and spring quarter, a sequence of interactive web/video modules substitutes the classroom lectures. In the winter quarter, the course is taught conventionally; both versions of the course are equivalent. Recommended: EE261, EE278B.
Office Hours: Monday, 11am - 12pm, in Packard 373
Office: Packard 359
(1) Problem session: Thursday, 4pm - 5pm, in Packard 277
(2) Drop-in: Monday, 4pm - 6pm, in Packard 353
Office Hours: Tuesday, 3pm - 5pm, in Packard 353
A new homework is released each Monday and is then due by 9:30am on the following Wednesday (after 9 days). Homework solutions should be written and submitted individually, but discussions among students are encouraged.
There will be 30% penalty for late homework submitted by Friday 9:30am.
You can submit the homework in class, in the EE368/CS232 drawer (2nd floor, near the kitchen area, Packard building), or by emailing a PDF document to email@example.com. If submitting electronically, please assemble all required responses (math, explanations, images, MATLAB code, etc.) into a single PDF document.
Graded homeworks will be returned in the EE368/CS232 drawer.
Dissemination of Course Information
The main class website (http://www.stanford.edu/class/ee368) contains all the course information, including lecture slides, assignments, and latest announcements.
Previously recorded lecture videos and interactive quizzes are available in the OpenEdX platform:
EE368/CS232 OpenEdX Website
All students enrolled in the class through Axess should be automatically placed on the email list firstname.lastname@example.org. We will send important announcements about the class through this list.
To facilitate open discussion of questions, we have also activated a Piazza account for this class:
The computers in the Stanford Center for Image Systems Engineering (SCIEN) Lab can be used to do your work in this class, although you can choose to use other university machines or your own computer. These machines are located in Room 021 (basement) of the Packard building. Room 021 is protected by a door key, which can be obtained by emailing the course staff. The SCIEN computers are equipped with MATLAB (with the Image Processing Toolbox) and the Android development environment. Another nice feature is that the SCIEN computers use the same username/password login as your normal Leland account, and all your regular files on the Leland network appear when you log into a SCIEN computer. The SCIEN machines can be remotely accessed (e.g., using SSH) by Rm021-2.stanford.edu through Rm021-20.stanford.edu, using your Leland username/password.
For basic tutorials on MATLAB, please look here. MATLAB can be run on the SCIEN machines by typing "/usr/local/MATLAB/R2011b/bin/matlab" from a command-line terminal.
For tutorials on Android which are customized for this class, please look here.
Please contact us if you have any questions about this page.
Last modified: 1/3/2014